Complete pathological response (pCR) is well recognized as the best intermediate endpoint to predict disease free survival. However, pCR has limitations which limit its utility for example for response guided therapy, including its availability only after therapy, and pCR response in <10% of ER+ve patients.
Despite their ability to reduce tumor size as assessed by palpation and imaging techniques [30], it is becoming increasingly apparent that by pCR criteria, primary systemic therapy with cytotoxic drugs increases disease free and overall survival in only a small a minority of breast cancer patients [31-33]. Since most breast cancer patients experience severe short-term and long-term side effects from chemotherapy [33-35] (whether or not treatment enhances survival benefit), there has long been a search for an effective intermediate endpoint for assessing chemotherapy response prior to or during treatment of breast cancer [36-38]. Given current evidence that switching regimens in nonresponders early in therapy can increase pCR rates and survival [39;40], the need for a test to reliably identify nonresponders to chemotherapy is becoming increasingly urgent. If this test (or another) can also accurately identify patients with chemotherapy-responsive tumors, then this would provide reassurance to patients with such tumors that the chosen treatment regimen is working.
Ribonucleic acids (RNA) are biopolymers which encode genetic information and play various roles in a cell, including encoding proteins. RNA preparations are employed in the investigation of gene expression, for example, by microarray experiments, RT-PCR and many other methods. The results of experiments employing RNA preparations and the significance of results obtained by such experiments, is largely dependent upon the integrity of the RNA employed. Different methods are available to measure RNA integrity of a sample. Typically the methods compare heat degraded or RNAse degraded samples to samples with intact RNA with regard to the capacity of the RNA at a particular degradation level to be sufficiently intact to permit PCR amplification of specific mRNAs such as “housekeeping” genes.
For example, Schroeder, A., O. Mueller, et al. (2006) [43] describes a method that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. The approach was applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to develop an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN) under certain conditions and/or for certain samples.
A method of using tumour RNA integrity to measure response to chemotherapy in cancer patients is disclosed in PCT/CA2008/001561 filed Sep. 5, 2008.